In the statistical analysis of data one often is confronted with observations that appear to be inconsistent with the remainder of that set of data (Barnett and Lewis, 1994). Although such observations (the outliers) have been subject of numerous investigations, there is no general accepted formal definition of outlyingness. Nevertheless, the outliers describe the abnormal data behaviour, i.e. data which are deviating from the natural data variability.Fil: Alves Rodrigues, Isabel Maria. Instituto Superior Tecnico. Department Of Mathematics; PortugalFil: Boente Boente, Graciela Lina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemática...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
Multidimensional outliers are observations considered to be rare not for their particular value in a...
This paper considers outliers in multivariate time series analysis. It generalizes four types of dis...
The term "outlier" is probably one of the vaguest and most imprecise ones in statistical science. Th...
The term "outlier" is probably one of the vaguest and most imprecise ones in statistical science. Th...
The term "outlier" is probably one of the vaguest and most imprecise ones in statistical science. Th...
hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the author and are ...
Data Science is the new and exciting interdisciplinary response that has emerged as a consequence of...
Outlier identification is important in many applications of multivariate analysis. Either because th...
Most outlier detection rules for multivariate data are based on the assumption of elliptical symmetr...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
[EN] Deviating multivariate observations are used typically to test the performance of outlier detec...
Multivariate outliers are usually identified by means of robust distances. A statistically principl...
\u3cp\u3eResearchers often lack knowledge about how to deal with outliers when analyzing their data....
The presence of outliers can very problematic in data analysis, leading statisticians to develop a w...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
Multidimensional outliers are observations considered to be rare not for their particular value in a...
This paper considers outliers in multivariate time series analysis. It generalizes four types of dis...
The term "outlier" is probably one of the vaguest and most imprecise ones in statistical science. Th...
The term "outlier" is probably one of the vaguest and most imprecise ones in statistical science. Th...
The term "outlier" is probably one of the vaguest and most imprecise ones in statistical science. Th...
hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the author and are ...
Data Science is the new and exciting interdisciplinary response that has emerged as a consequence of...
Outlier identification is important in many applications of multivariate analysis. Either because th...
Most outlier detection rules for multivariate data are based on the assumption of elliptical symmetr...
Researchers often lack knowledge about how to deal with outliers when analyzing their data. Even mor...
[EN] Deviating multivariate observations are used typically to test the performance of outlier detec...
Multivariate outliers are usually identified by means of robust distances. A statistically principl...
\u3cp\u3eResearchers often lack knowledge about how to deal with outliers when analyzing their data....
The presence of outliers can very problematic in data analysis, leading statisticians to develop a w...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
Multidimensional outliers are observations considered to be rare not for their particular value in a...
This paper considers outliers in multivariate time series analysis. It generalizes four types of dis...